Categoría: Software development

It’s hard to overestimate this language also from a server-side perspective, where Node.js as a JavaScript runtime environment is a great fit. Given all the above, it’s easy to assume why JavaScript developers in Ukraine are in great demand. They are able to successfully cover a wide range of issues related to the development of state-of-the-art software solutions.

The current situation confirms the high demand for web development specialists and the availability of a large number of jobs. For example, in the U.S., the demand for JavaScript developers in 2020 increased by 17% compared to previous years. Below we will consider the issue of developers’ salaries in more detail. Be prepared to pay between $78,000 and $120,000 a year for a good JS developer in the US.

Hire the Node.js developers you need for your next project through K&C

Eastern Europe has traditionally been a popular nearshore IT outsourcing destination for higher salary economies from Western Europe. Large numbers of North American employers of software developers and other IT specialists have also been attracted to the region due to its attractive combination of lower costs and deep talent pool. Particularly junior or senior Node.js developers would command salaries in the bottom and top 25 percentiles respectively. Ever wondered which is the most demanded programming language in 2023? Although there are more than 200+ programming languages, only few of them are used in the real world industry. Knowing this information is essential to succeed in the developer job industry.

As everywhere in the world, figures in France vary depending on the experience and skills of the developers you are about to hire, as well as their location. As it has been time and again proven by studies, JavaScript developers located in capitals and other large cities are more highly paid than those in small towns and provinces. The USA is both the world’s biggest economy and the world’s biggest tech labour market, employing far more software developers and other IT specialists than any other country. But despite having the world’s deepest pool of IT talent it also has the tightest IT labour market with demand outstripping supply by a greater margin than anywhere else.

All Remote JavaScript Jobs Latest post about 16 hours ago

What if we say that the only difference between JavaScript developers all over the world is the salary rate, while they are pretty similar in terms of the quality of work they perform? When hiring the DDI Development team you will get high-devoted professionals as a remote team yet totally engaged in your project. When considering the pay levels for software engineers across many European countries, France is one of those to keep an eye on.

• According to Glassdoor, the average Vue.js developer salary in the US is $78,526.
• Just take a look at these figures when deciding on the development team to work with.
• When you hire a JavaScript programmer, it is important to ask them the correct questions in the interview round.
• It is also heavily used in the blockchain ecosystem, Bitcoin or the Solidity Smart Contract language are written entirely with C++.
• At the same time, there is a slight difference in salaries of specialists with 19 years of experience and specialists with more than 20 years of experience.
• They should understand refactoring, design patterns, and architectural paradigms and have experience with infrastructural maintenance and server deployments.

It is used to write the logic behind the smart contracts that runs in most of the blockchains nowadays. When you hire a JavaScript programmer, you will be able to satisfy various needs in your mobile and web application. In short, a full stack JavaScript developer should be able to develop client as well as server software. Apart from possessing proficiency in HTML and CSS, the person should also know the techniques of programming a browser (using jQuery, JavaScript, Vue or Angular) and server (using Node).

Understanding JavaScript as a programming language

Europe’s largest economy, Germany is also second only to the UK as a market for software development talent. Software developers with Node.js expertise are therefore in high demand. That has pushed software developer salaries in the USA to high levels, which is reflected in the average salary range enjoyed by Node.js developers in the country.

Due to a vast talent pool and solid experience in programming, tech giants decide to expand their business there, successfully managing offshore teams. Leading remote teams is not a challenge for them due to the programmers’ soft skills, such as independence, ability to work in a team, and good English skills. Another factor that reinforces this perfect match is cultural similarities.

Jr. Frontend Software Engineer

The market potential of JavaScript developers is another noteworthy topic. I suggest analyzing it through the lens of supply and demand in the labor market. They should understand refactoring, design patterns, and architectural paradigms and have experience with infrastructural maintenance and server deployments. Developers with these skills will continue to remain desirable and paid accordingly.

Naturally, not all JavaScript developers are equal, and skills and background also affect salaries. To sum up, a JavaScript developers salary in Europe is around half of a comparable salary in the US. Finally, Indeed data on the average base JavaScript programmer salary places it at $108,618 annually. Such high demand has forced industry players to increase developer salaries in order to attract talent. Read on to discover the state of the market and how you can reduce the JavaScript developer’s salary you have to pay without compromising on the security of your code. Now that we’ve covered that continent, let’s take a trip east across the ocean to see the state of average JavaScript developer salaries in Europe.

Average JavaScript developer salary in Canada

At the same time, the specialists are usually very skilled and can fulfill tasks of any difficulty. Full-stack developers are paid almost the same as the ones from Ukraine. It includes the salary ranges and availability of the requested developers in Poland, Romania, and other countries in EE (as well as time-to-hire metrics and other KPIs for your case). Entry-level JavaScript developers in Germany with less than two years of experience can expect an average salary of € per year. This is 3.2%, or €1 180, less than an entry-level Python developer’s salary of €37 004, and 9.82%, or €3 901, less than their Java equivalents.

When considering tech talents from all over the world, it would be reasonable to consider the level of salaries for JavaScript developers in Canada as well. The average pay local specialists make is about $104k per year, while the lowest rate is $41k and the highest is $194k. javascript developer salary europe What’s more, our research on the average Node.js developer salary uncovered some uncomfortable data from the US Bureau of Labor Statistics. It turns out that in 2020, employers spent nearly 30% on worker benefits and compensations—over and above their stated salaries.

How much do remote JavaScript developers earn In Europe?

From 01-October-2021 to 01-October-2022 (1 year), DevJobsScanner has analyzed more than 10M dev job offers from around the world to help us understand the market and the most trending and paid languages. Below you can see a chart with selected countries in Europe and the average salary for web developers in each one of them, the salaries are gross in Euros per month. A significant difference in salary rates is the crucial factor to consider. In the UK, a mid-level JS developer will cost you $71,000 and $64,000 in Germany, while in Poland a coder with the same level of expertise costs $36,000.

You will be the point person for all technical inquiries and will be responsible for ensuring that all team members are up-to-date on the latest technical developments. In addition, you will be responsible for developing and implementing technical training programs for team members. Technical team leaders will need to stay up-to-date on these developments to keep their skills relevant and maintain a competitive advantage in the workplace. Providing technical leadership to ensure that projects are delivered to a high standard. The two will most likely collaborate closely on the technical roadmap.

The Tech lead role includes responsibilities such as business development, planning, designing, leading, and implementing technical solutions and improvements. As Tech Lead, expect to dedicate a lot of time to fielding questions about technical aspects and conducting code reviews. It’s an interpersonal role, requiring you to rely on your soft skills, technical skills, and leadership skills in equal parts. The engineering manager also plays an important role in determining if a feature can be built by the team by a certain point in time.
We are looking for candidates that are experienced front-end developers with some knowledge of back-end technology. A tech lead is closer to management than an individual contributor. So, you want to look for someone who shows strong signals for good management work. Much like any other management, don’t expect the perfect candidate to fall in your lap. Just like any other role, you’ll need to grow your tech lead’s competence over time.
They should help guide the team through technical decisions, not silo themselves and dictate solutions. As a tech lead, I realised that having a deeper understanding of technology and being able to communicate that understanding with my team effectively was essential for our success. It helped me build trust and rapport with my colleagues, fostering an environment of innovation and growth. This collaborative atmosphere enabled us to work together more efficiently, breaking down barriers and encouraging open dialogue. Tech leaders take care of keeping up with the latest technologies and industry trends, fostering a culture of leadership within my organisation and creating meaningful value to our customers, partners and employees. Once team members know what to do, it is time for tech leads to focus on delivering value.

Job summary 6

Engineers with a proven growth mindset have better chances to become tech leads. In the meantime, give yourself a break when it comes to how much code you write, how good your code is, or how well you know the technology. Instead, focus on getting good at the tasks now under your purview. Can you identify underperforming teammates and flag that to your manager? Are you aware of any skill gaps on your team and have you flagged that to your manager?
Since code is easier to measure than your new responsibilities, it’s easy to get down on yourself about what feels like a decrease in productivity. Tech Lead is an incredibly collaborative role, not just within the team, but also between teams. In order to achieve teamwork on an organizational level, Tech Lead should act as a point of contact for other engineering teams. Assisting with the development of project plans, budgets, and schedules. Overseeing the design, development, testing, and deployment of software applications. The Technical Lead directs and coordinates the activities of tool and die makers/mechanics relative to the machinery and duties within the department and gives input for all technical aspects by performing the following duties.

• Moreover, a good Tech Leader will act as a buffer zone between stakeholders and team members, enabling the former to focus on their actual deliverables.
• They also ensure that the custom app development process is efficient and effective, enabling teams to deliver high-quality software on time and budget.
• Valuable insights into these activities enable you to move from a feeling-driven to a data-driven leadership approach and analyze metrics that matter.
• A DevOps/SRE tech lead is typically a seasoned engineer in charge of leading the team’s efforts towards achieving a common goal while providing on-keyboard impact.
• If they’d like to focus instead more on coding, they may choose to stop being a tech lead, at least temporarily.

Last year, I attempted to create a tech lead job description at Miquido. As I was promoted to team leader and became responsible for the entire backend development team, I realised that I alone could only provide technical guidance for some of the technologies we use as backend services. The technical lead job description might sound different, from one company to another, but some things remain constant.

The Tech Lead Job Description

As a Tech Lead, you need to frequently talk with every team member, not just the technical details, to get to know each team member’s strengths, weaknesses, and interests. Every company has an origin story, and many times, businesses launch because there’s a gap in the market. Another tricky social situation is when fellow coders argue, you may need to help referee and break stalemates.

The Technical Lead will oversee our technical team, provide direction and guidance for development projects, and ensure that all projects meet the highest quality standards. The ideal candidate will be a creative thinker to provide innovative solutions to complex development challenges. As a technical team leader at [CompanyX], you will be responsible for the day-to-day management and supervision of a team of engineers and technicians.

Role as a Team Leader

They ensure the software development process aligns with best practices, coding standards, and business needs and stay up-to-date with industry trends to maintain a competitive edge. Additionally, their role involves empowering and developing team members into future leaders through mentorship, growth opportunities, and a supportive work environment. They have extraordinary experience in creating software, resulting in an in-depth understanding of the development process, from conception to deployment. Tech leaders know how to collaborate with teams, identify and solve problems, and make strategic decisions to ensure the success of their projects. Additionally, tech leaders must excel with solid communication skills, allowing them to convey complex technical concepts to technical and non-technical stakeholders effectively.
In this article, we’ll break down the responsibilities and requirements of a tech lead to figure out if it’s the right fit for you. The employment of technical team leaders is expected to grow much faster than average over the next decade. We’re seeking a skilled and motivated lead web developer to join our eCommerce Engineering Team within the Global Direct-to-Consumer organization. The Dev team is responsible for the online shopping experience of sites around the globe with further expansion on the horizon.

The need for more technical talent is a trend that is being driven by the increasing complexity of technology. As businesses become more reliant on technology, they will need to hire professionals who can manage and maintain their systems. Their close proximity with developers will allow them to make informed decisions on legacy code or software quality issues. A lot of ink has been spilled on the differences between a tech lead and a team lead.

The tech lead, because they spend so much time in the codebase, will be able to explain what debt needs to be addressed and how, and the engineering manager will translate that into a priority to be communicated to leadership. Tech leads not only play a crucial role within the development team but also have a significant impact on client relations. Technical leaders help create strong, mutually beneficial partnerships that drive business growth and success by acting as a bridge between clients and development teams. With more than 1,000 new packages being added to NPM repositories daily, keeping up to date with all tech newbies is impossible.

A lot of developers want to become technical leaders at some point in their careers. Which is all well deserved if you are at that point in your career. https://www.globalcloudteam.com/ Technical leaders, as a rule, are engineers who have gained authority in the team with their fresh ideas, initiative, and high performance.

They commonly act as a liaison between their team and upper management, ensuring that everyone is on the same page with regard to company goals and objectives. In my personal experience, it’s difficult to be both an effective coder while also serving as a tech lead for a productive team. A productive team means that the tech lead will need to spend a lot of time collaborating with engineers on their own team and other teams and answering questions from both outside and within the team.

The
underscore lets Sass know that the file is only a partial file and that it
should not be generated into a CSS file. CSS on its own can be fun, but stylesheets are getting larger, more complex, and
harder to maintain. Sass has features
that don’t exist in CSS yet like nesting, mixins, inheritance, and other nifty
goodies that help you write robust, maintainable CSS. Still not sure what direction you’d like to go in your development career?

Based on research released earlier this year, the average employee uses 28 different SaaS applications, and in mid-size organizations, seven new applications are introduced each month. This massive pool of data is at the core of the company’s technology, enabling them to provide insights into applications, their usage patterns across hundreds of companies, and actionable remediation. As you’ll learn in a moment, Sass allows for variables and chunks of code that can be reused over and over again. This saves developers a lot of time and reduces the risk of coding mistakes. It also makes it easier and faster to change styles in multiple places in your code, such as frame sizes, border styles, colors, and so on. When business leaders are in the market for a new software as a service solution, it can be tempting to quickly sign up with a provider that looks promising so they can start leveraging the benefits.

‘Which company functions do you automate?’

In future web pages, all you need to do is call out the Mixin rather than remembering to individually call the font, color, and border values. This means when you run Sass code, you’re actually converting your code to CSS. That CSS code output is then used directly by a browser. Think of Sass as a programming “dialect” rather than a whole new language. If you already know CSS, then you’ll be relieved to find that a lot of Sass syntax is identical to CSS.

To create a mixin you use the @mixin directive and give it a name. We’re also using the variable $theme inside the parentheses
so we can pass in a theme of whatever we want. After you create your mixin,
you can then use it as a CSS declaration starting with @include followed by
the name of the mixin.

VariablesVariables permalink

Functions accept inputs from the user and run through specific lines of code to perform complex operations. “We serve hundreds of companies with our Shadow-IT tier, and we studied their SaaS environments and needs.” Galit Lubetzky Sharon, CEO of Wing. And then, finally, there’s the constant updates, upgrades and other maintenance things which make classic software models even costlier and more of a pain. Delivering free updates is painful and tedious and often ineffectual, and upgrades to new versions cost yet more money companies and private users do not want to pay. With our cloud-native AI and analytics platform, you can understand what’s happening with your data now, predict how to pivot seamlessly, and make progress faster. Regardless of role, everyone in your organization will feel the impact of increased performance and productivity.

The most direct way to make this happen is in your terminal. Once Sass is
installed, you can compile your Sass to CSS using the sass command. You’ll
need to tell Sass which file to build from, and where to output CSS to. For
example, running sass input.scss output.css from your terminal would take a
single Sass file, input.scss, and compile that file to output.css. To get into the chatbot development, you’ll need to have a good command of these programming languages.

years of analytics innovation

Therefore, a Sass file must first be compiled into CSS before being used in an HTML document. This can be done locally before uploading the CSS to the web server using program like Compass.app or Koala. It can also be compiled on the server using a PHP or Ruby script that compiles Sass into CSS. Sass is the short form of Syntactically Awesome Style Sheet.

• Below, 20 members of Forbes Technology Council share important questions to ask a potential SaaS vendor and what to listen for in their replies.
• For example, if you have multiple styles that are the same color, you need to define the color separately for each style.
• B – You know the levels of permissions given to them and how many employees are using them.
• Instead of retyping changes over and over in CSS, you can simply change the value of your variable of interest in Sass.
• It uses fully-compatible CSS syntax, but provides additional features like CSS variables and nested rules that make CSS more efficient and easier to edit.

Both syntax styles allow you to use variables, Mixins, functions, and other features not available in native CSS. There’s still hot debate on whether CSS counts as a full programming language. But, no https://www.globalcloudteam.com/ matter where you stand on the topic, it’s easy to see that CSS was designed to provide instructions on how a web page should look rather than to perform decision-making tasks and work with variables.

Understand Generative AI: What it is and why it matters.

While everything done in Sass can be done in CSS, Sass helps you, the developer, write code in a way that looks and feels like a programming language. Rather than coding in individual instructions on every page, Sass functions allow you to code in the instructions once. Later on, it’s easy to call your function to perform the same task as many times as you need to. Sass allows you to define variables so you can easily change key values later, such as color, font size, and borders.

Using @extend lets you share a set of CSS properties from one selector to
another. In our example we’re going to create a simple series of messaging for
errors, warnings and successes using another feature which goes hand in hand
with extend, placeholder classes. A placeholder class is a special type of class
that only prints when it is extended, and can help keep your compiled CSS neat
and clean.

Learn how computer vision gives manufacturers another set of eyes.

Sass (Syntactically Awesome Style Sheets) is an extension of CSS. Style sheet languages control where and how text appears on a webpage, from frame size and color to menu positions. But these aren’t the only useful tools for Front-End Developers. sass technology Many people who learn CSS go on to learn Sass for more efficient and consistent web design, especially for large, complex web development projects. Sign up for free and start receiving your daily dose of cybersecurity news, insights and tips.

Sass (short for syntactically awesome style sheets) is a preprocessor scripting language that is interpreted or compiled into Cascading Style Sheets (CSS). Today, mid-sized companies and their CISOs are struggling to handle the growing threat of SaaS security with limited manpower and tight budgets. By focusing on the critical SaaS security needs of these companies, a new approach has emerged that can be launched for $1,500 a year. SaaS is changing the way software and marketing works on a grand scale, so everyone needs to know a little bit about it, even if it doesn’t directly relate to their field. Modernize with your cloud provider of choice for faster, secure access to your data. SAS continues to advance our technologies and bring trusted analytics to companies that impact our everyday lives – so that customers can count on us when it matters most.

SaaS security must-haves: Discover, Asses, Control

While there are a few key differences between the two, most developers who already know CSS can pick up Sass after taking a brief course. At W3Schools you will find complete references of all Sass functions with syntax and examples. Our “Show Sass” tool makes it easy to learn Sass, it shows both the code and the result. Use our color picker to find different RGB, HEX and HSL colors. Sass allows for iterating over variables using @for, @each and @while, which can be used to apply different styles to elements with similar classes or ids.

One of the common misconceptions concerning financial data is that it is all numerical. While this might be the case with things like accounting ledgers, most data exists in the form of text which is largely unstructured. And one recent survey indicates that 90% of the world’s central banks are grappling with how to derive value from their unstructured data. Consider, for example, the numerous written reports that investment managers and traders need to comb through to make informed decisions, or the many external communications with clients that take place over email and chat. Few sectors are nearly as data heavy as finance, an area that oversees hundreds of millions of transactions every day.

Align processes and performance management to adjust for AI’s inclusion on the team. Both the chief investment officer and portfolio managers should be onboard to help with challenges and integrate the technology and investment teams. Once the objectives of NLP/G adoption are truly shared, an organization can pursue them in a coordinated fashion.11 Close collaboration between technology, investment, data science, and strategy teams can help drive NLP and NLG adoption.

Financial Sentiment

NLP for financial documents aids in automated compliance checks by extracting relevant information from legal texts and policy documents, ensuring adherence to intricate regulatory frameworks. NLP algorithms identify patterns in large volumes of textual data to detect fraudulent activities. Financial institutions can swiftly pinpoint suspicious activities and prevent fraud by analyzing transaction narratives and customer communications. To use the mining analogy, NLP/G performs a refining step that concentrates the ore before analysts spend time on evaluation.

Unstructured information within a bank poses challenges when it comes to extracting insights and this is where NLP comes in. Equity performance is one area of that banks need attention and NLP tools provide a clear analysis of operations. By using NLP for market forecasting, HSBC explores stock market performance and offers recommendations based on prevailing market conditions. The success of companies in the financial industry depends on risk management procedures adopted and NLP is supporting in this area. Unlike the past when banks took long to get the whole market view, NLP is streamlining the process through #data extraction tools.

Artificial intelligence and machine learning in the banking and financial industries: use cases

Retrieving information from unstructured resources that financial institutions have problems accessing. Credit scoring seems to be one of the more common applications for AI in finance, and vendors now are offering products that can help assess credit scores for customers with little or no credit history. Many of these products use NLP to gauge the creditworthiness of a customer from their digital footprints. He holds a PhD in Environmental Shareholder Value from the University of Freiburg.

When these two technologies are coupled, they can successfully handle massive volumes of data. Every investor’s main aim is to maximize their wealth over time without being aware of the underlying distribution provided by stock prices. Data science, machine learning, and nonparametric statistics can be used to anticipate investment strategies in financial stock markets. NLP is a very effective way to predict time series such as stock prices in the financial sector. It has the unique ability to determine complex nonlinear relationships and to accurately approximate nonlinear functions.

Data Quality

For example, NLP can analyze vast amounts of publicly available feedback on social media, public forums, and consumer review websites, to broadly determine how clients feel about a particular brand. In a sector where trust is everything, financial institutions can never be too aware of how their reputations stack up against the competition. Natural language processing is the key to unlocking the value https://www.globalcloudteam.com/ in this data—it’s a powerful solution for making sense of this wealth of data at machine speed by adding context that makes it searchable and actionable. For example, a model might be trained to flag sections of text that address specific areas of interest, such as financial risk or client sentiment. A leading investment firm followed many of these principles in their path to NLP/G adoption.

Today, companies use Artificial intelligence (AI) approaches to spend less time on data discovery and more time on deriving insights from the data. It streamlines that process, extracting relevant entities and interpreting them within the context of the document. The machine learning model trained with historical underwriting data then evaluates the extracted information, detecting potential red flags and helping the agents assess the risks related to the particular case. With NLP, machines extract the information from the user’s writing or speech in real-time and generate the relevant answers.

How NLP is Transforming the Finance Industry

Banks make decisions based on NLP tools, which further accelerates the preparation of financial reports. Banks need accurate information about their operations and NLP tools are changing the landscape by helping them make decisions based on customer and market trends. Companies such as Green Key Technologies have developed NLP solutions for the financial industry with their latest innovation around trading desks. Financial institutions use their tools in voice information and analysis of trading processes.

• These are becoming increasingly sophisticated and difficult to pick up as a result, particularly with the substantial volume of applications waiting to be reviewed.
• The system then provides a summary of the most relevant information for search queries from employees at financial firms on the search engine interface.
• Routine operations, such as anti-money-laundering (AML) and know-your-customer (KYC) checks, are taking longer and demanding comprehensive oversight and transparency.
• We hope that this article allows business leaders in finance to garner insights they can confidently relay to their executive teams so they can make informed decisions when thinking about AI adoption.
• The machine learning model trained with historical underwriting data then evaluates the extracted information, detecting potential red flags and helping the agents assess the risks related to the particular case.
• Information search and discovery can be a highly viable AI solution for finance companies.

NLP/G technology is most mature in the postinvestment phase, with applications already in use at some large investment management firms. Because portfolio and index performance are naturally structured data, NLP/G engines can readily use these inputs to generate performance attribution reports and periodic investor reviews. These outputs’ programmatic nature combined with NLG’s ability allows for the creation of client on-demand reporting. Figure 4 shows a machine-generated portfolio narrative that was written with NLP/G technology and made available to investors shortly after period close. As the investment management industry increasingly adopts AI solutions, new technologies—including natural language processing—are helping investment analysts with their most “human” responsibilities, including making investment decisions. Text is unstructured data, and it’s inherently harder to use unstructured data, which is where natural language processing comes into play, Shulman said.

WHO IS A CHIEF DATA OFFICER AND DOES YOUR COMPANY NEED ONE?

Natural language processing (NLP) models can be trained to review unstructured content, and spot issues or trends that may impact financial markets. Practical examples of natural language processing in action include speech recognition and intent parsing used by voice assistants and chatbots in customer services, and information retrieval and sentiment analysis of corporate documents and news feeds. NLP techniques and algorithms help to translate the raw textual data into meaningful insights across several areas in finance. Traders, portfolio managers, analysts, banks and other financial organizations strive to improve their financial analysis, and NLP and ML have become the technologies of choice. NLP is used across the financial industry, from retail banking to hedge fund investing. Such NLP techniques as sentiment analysis, question-answering (chatbots), document classification and topic clustering are used to work with unstructured financial data.

To gather useful investment data, the NLP-powered search engine extracts the components, concepts, and notions included in these papers. When environmental parameters are unclear, it assists in achieving the highest potential growth rate. By filtering out good and unattractive equities, data envelopment analysis may be used to select a portfolio. The data gathered in the past may be utilized to forecast the start of a trading session and a portfolio. Investors can disperse their present capital among the various assets using this information.

Reshaping text analytics – is AI a game changer for analysts?

In the last five years, several deep learning algorithms have begun to outperform humans in a variety of tasks, including speech recognition and medical picture analysis. Recurrent neural networks (RNN) are a particularly successful approach of forecasting time series, such as stock prices, in the financial realm. From retail banking to hedge fund investment, NLP is employed in the financial industry. To work with unstructured financial data, NLP techniques such as sentiment analysis, question-answering (chatbots), document categorization, and topic clustering are utilized. Sentiment analysis helps to categorise news based on positive and negative sentiment and shows potential impacts on stock prices, but it also has more subtle uses like retrieving customer emotions and testimonials on products. NLP allows procurement of customer feedback and taking crucial financial decisions based on customer testimonials.